Within the framework of the ad hoc business climate research program started by IEER, we examined the estimation possibilities of the unemployment situation in Hungary by Google Insights for Search (GIS) application. In Hungary the Hungarian Central Statistical Office discloses data on unemployment on a quaterly basis and are published in the middle of the quarter that follows the relevant quarter. It would be useful to achieve results earlier on the unemployment level experienced during each quarter. GIS would be the solution for this since it is capable to demonstrate the keywords and the number of Google searches in time and field breakdown. The esteemability of unemployment is backed by the assumption that job search is done partly through the internet. In the research program all our keywords were in connection with job search. Besides, we examined two indices related to the labour force market: one on the unemployment data, the other on the number of registered job seekers. The outcome of these models – compared with our basic model – show that we can achieve a lot better one if we do utilize the information acquired on the search activity. Accordingly, in the unemployment estimation process the models estimated by GIS data reached a better goodness-of-fit than the other type of models.